1. Field of the Invention
This invention generally relates to video decoding and, more particularly, to a method for maintaining relatively lossless video decoding using computation-reduced inverse discrete cosine transformation process.
2. Description of the Related Art
Complexity-scalable image/video decoding techniques are essential to applications where computation power is limited, and/or full resolution quality images are not necessary. Discrete cosine transform (DCT) processes are used in many popular image/video-coding systems, such as JPEG, MPEG-1-2-4, and H.263 systems. Inverse discrete cosine transform (IDCT) processing is widely recognized as one of the most computation-demanding processes of the image/video decoders. Conventionally, the approaches have been developed to simplify the IDCT process and save computation result in a trade off of added visual artifacts and a loss of resolution.
FIG. 1 is a drawing that illustrates a conventional two-dimensional (2D) 8×8 IDCT process (prior art). The 8×8 DCT coefficients undergo 8 horizontal one-dimensional (1D) IDCT transforms, followed by 8 vertical 1D IDCT transforms, to generate 8×8 image residuals in the space domain. In total, 16 1D IDCT operations are needed. Since the horizontal and vertical transforms are independent of each other, the same result is achieved if the process is begun with the vertical transforms and finished with horizontal transforms. The following discussion, however, will follow the process explicitly depicted in FIG. 1
The key to computation reduction is in the reduction of the number of 1D IDCT operations. The most straightforward way to reduce the number of IDCT computations is to set some of the high frequency DCT coefficients to zero value.
FIG. 2 depicts a few examples of reduced complexity DCT coefficient masks (prior art). The coefficients in the non-shaded area are set to zero value to reduce computation complexity. For example, when the 4×8 mask is applied, the resultant 2D IDCT process requires 4 horizontal and 8 vertical IDCT operations. In total, 12 1D IDCT operations are required. However, as we mentioned above, the trade-off associated with a reduction in complexity is the degradation of visual quality. The visual artifacts become very annoying when strong image edges (such as the letter box boundary in movie materials) are present. For example, using a reduced complexity mask to decode a frame with a letter box boundary may result in the appearance of dark stripes in the image. These stripes are artifacts of the letter box boundary.
It would be advantageous if a reduced complexity IDCT process could be developed that didn't significantly degrade the decoded video image.